Energy-Efficiency Formation Control of AUVs via Angle Measurement: A Minimally Rigid-Based Solution
Formation control of autonomous underwater vehicles (AUVs) has been regarded as the basis of many sophisticated marine missions. However, the complex marine environment and the high communication energy consumption make it hard to achieve this task. This article is concerned with an energy-efficiency formation issue of AUVs via angle measurement. Particularly, the single vector hydrophone is used to measure the single-frequency signal emitted by AUVs, through which the relative angles among AUVs can be estimated. Based on this, a minimally angle rigid topology generation algorithm is designed to balance the tradeoff between communication energy efficiency and topology connectivity, while a model-free inverse reinforcement learning (IRL)-based formation controller is developed to steer AUVs to reach the target while maintaining a specific shape. The innovations are summarized as follows: 1) the angle measurement in this article can eliminate the reliance on the position information of AUVs; 2) the minimally angle rigid topology in this article can improve the formation stability and reduce the communication energy consumption as compared to the neighboring rule-based solutions; and 3) the IRL-based controller can avoid manually designing cost functions and improve environmental adaptability as compared to traditional-learning-based controllers. Finally, simulation and experimental results are both conducted to verify the effectiveness.
Authors
- Cailian Chen (ORCID: https://orcid.org/0000-0001-6533-8713)
- Xiaoyuan Luo (ORCID: https://orcid.org/0000-0003-0404-9533)
- Xinping Guan (ORCID: https://orcid.org/0000-0003-1858-8538)
- Jing Yan (ORCID: https://orcid.org/0000-0001-7768-5720)
- Xian Yang (ORCID: https://orcid.org/0000-0002-9595-7280)
- Zexing Tian
Institutions
- Shanghai Jiao Tong University (CN)
- Yanshan University (CN)
Publication Details
- Journal
- IEEE Transactions on Systems Man and Cybernetics Systems
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1109/tsmc.2025.3598281
- Primary Topic
- Distributed Control Multi-Agent Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Department of Education of Hebei Province
- Natural Science Foundation of Hebei Province